Edge computing and analytics are fascinating the whole world of computing. Industry and business are keenly embracing this sound concept to develop customer-centric solutions by enhancing their operations, offerings, and outputs. There is a bevy of advancements in this domain that came with the arrival of IoT devices. The seamless convergence of microservices and serverless computing creates vast opportunities. With the help of IoT devices and these other developments, there has become a deep interest in business automation and additional improvisations in edge computing. With the steady growth of edge devices and applications of IoT fog/edge computing and analytics, there are also distinct challenges and threats. Research has been keenly focused on identifying and understanding these issues and shortcomings to bring viable solution approaches and algorithms. Cases on Edge Computing and Analytics describes the latest innovations, improvements, and transformations happening with edge devices and computing. It addresses the key concerns of the edge computing paradigm, how they are processed, and the various technologies and tools empowering edge computing and analytics. While highlighting topics within edge computing such as the key drivers for implementation, computing capabilities, security considerations, and use-cases, this book is ideal for IT industry professionals and project managers, computer scientists, computer engineers, and practitioners, stakeholders, researchers, academicians, and students looking for research on the latest trends and transitions in edge computing.

With the rapid development of big data, it is necessary to transfer the massive data generated by end devices to the cloud under the traditional cloud computing model. However, the delays caused by massive data transmission no longer meet the requirements of various real-time mobile services. Therefore, the emergence of edge computing has been recently developed as a new computing paradigm that can collect and process data at the edge of the network, which brings significant convenience to solving problems such as delay, bandwidth, and off-loading in the traditional cloud computing paradigm. By extending the functions of the cloud to the edge of the network, edge computing provides effective data access control, computation, processing and storage for end devices. Furthermore, edge computing optimizes the seamless connection from the cloud to devices, which is considered the foundation for realizing the interconnection of everything. However, due to the open features of edge computing, such as content awareness, real-time computing and parallel processing, the existing problems of privacy in the edge computing environment have become more prominent. The access to multiple categories and large numbers of devices in edge computing also creates new privacy issues. In this book, we discuss on the research background and current research process of privacy protection in edge computing. In the first chapter, the state-of-the-art research of edge computing are reviewed. The second chapter discusses the data privacy issue and attack models in edge computing. Three categories of privacy preserving schemes will be further introduced in the following chapters. Chapter three introduces the context-aware privacy preserving scheme. Chapter four further introduces a location-aware differential privacy preserving scheme. Chapter five presents a new blockchain based decentralized privacy preserving in edge computing. Chapter six summarize this monograph and propose future research directions. In summary, this book introduces the following techniques in edge computing: 1) describe an MDP-based privacy-preserving model to solve context-aware data privacy in the hierarchical edge computing paradigm; 2) describe a SDN based clustering methods to solve the location-aware privacy problems in edge computing; 3) describe a novel blockchain based decentralized privacy-preserving scheme in edge computing. These techniques enable the rapid development of privacy-preserving in edge computing. .

This book provides the state-of-the-art development on security and privacy for fog/edge computing, together with their system architectural support and applications. This book is organized into five parts with a total of 15 chapters. Each area corresponds to an important snapshot. The first part of this book presents an overview of fog/edge computing, focusing on its relationship with cloud technology and the future with the use of 5G communication. Several applications of edge computing are discussed. The second part of this book considers several security issues in fog/edge computing, including the secure storage and search services, collaborative intrusion detection method on IoT-fog computing, and the feasibility of deploying Byzantine agreement protocols in untrusted environments. The third part of this book studies the privacy issues in fog/edge computing. It first investigates the unique privacy challenges in fog/edge computing, and then discusses a privacy-preserving framework for the edge-based video analysis, a popular machine learning application on fog/edge. This book also covers the security architectural design of fog/edge computing, including a comprehensive overview of vulnerabilities in fog/edge computing within multiple architectural levels, the security and intelligent management, the implementation of network-function-virtualization-enabled multicasting in part four. It explains how to use the blockchain to realize security services. The last part of this book surveys applications of fog/edge computing, including the fog/edge computing in Industrial IoT, edge-based augmented reality, data streaming in fog/edge computing, and the blockchain-based application for edge-IoT. This book is designed for academics, researchers and government officials, working in the field of fog/edge computing and cloud computing. Practitioners, and business organizations (e.g., executives, system designers, and marketing professionals), who conduct teaching, research, decision making, and designing fog/edge technology will also benefit from this book The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, and information systems, but also applies to students in business, education, and economics, who would benefit from the information, models, and case studies therein.

With the rapid development of big data, it is necessary to transfer the massive data generated by end devices to the cloud under the traditional cloud computing model. However, the delays caused by massive data transmission no longer meet the requirements of various real-time mobile services. Therefore, the emergence of edge computing has been recently developed as a new computing paradigm that can collect and process data at the edge of the network, which brings significant convenience to solving problems such as delay, bandwidth, and off-loading in the traditional cloud computing paradigm. By extending the functions of the cloud to the edge of the network, edge computing provides effective data access control, computation, processing and storage for end devices. Furthermore, edge computing optimizes the seamless connection from the cloud to devices, which is considered the foundation for realizing the interconnection of everything. However, due to the open features of edge computing, such as content awareness, real-time computing and parallel processing, the existing problems of privacy in the edge computing environment have become more prominent. The access to multiple categories and large numbers of devices in edge computing also creates new privacy issues. In this book, we discuss on the research background and current research process of privacy protection in edge computing. In the first chapter, the state-of-the-art research of edge computing are reviewed. The second chapter discusses the data privacy issue and attack models in edge computing. Three categories of privacy preserving schemes will be further introduced in the following chapters. Chapter three introduces the context-aware privacy preserving scheme. Chapter four further introduces a location-aware differential privacy preserving scheme. Chapter five presents a new blockchain based decentralized privacy preserving in edge computing. Chapter six summarize this monograph and propose future research directions. In summary, this book introduces the following techniques in edge computing: 1) describe an MDP-based privacy-preserving model to solve context-aware data privacy in the hierarchical edge computing paradigm; 2) describe a SDN based clustering methods to solve the location-aware privacy problems in edge computing; 3) describe a novel blockchain based decentralized privacy-preserving scheme in edge computing. These techniques enable the rapid development of privacy-preserving in edge computing.

This reference text presents the state-of-the-art in edge computing, its primitives, devices and simulators, applications, and healthcare-based case studies. The text provides integration of blockchain with edge computing systems and integration of edge with Internet of Things (IoT) and cloud computing. It will facilitate readers to setup edge-based environment and work with edge analytics. It covers important topics, including cluster computing, fog computing, networking architecture, edge computing simulators, edge analytics, privacy-preserving schemes, edge computing with blockchain, autonomous vehicles, and cross-domain authentication. Aimed at senior undergraduate, graduate students and professionals in the fields of electrical engineering, electronics engineering, computer science, and information technology, this text: Discusses edge data storage security with case studies and blockchain integration with the edge computing system Covers theoretical methods with the help of applications, use cases, case studies, and examples Provides healthcare real-time case studies elaborated by utilizing the virtues of homomorphic encryption Discusses real-time interfaces, devices, and simulators in detail

This book presents state-of-the-art research on security and privacy- preserving for IoT and 5G networks and applications. The accepted book chapters covered many themes, including traceability and tamper detection in IoT enabled waste management networks, secure Healthcare IoT Systems, data transfer accomplished by trustworthy nodes in cognitive radio, DDoS Attack Detection in Vehicular Ad-hoc Network (VANET) for 5G Networks, Mobile Edge-Cloud Computing, biometric authentication systems for IoT applications, and many other applications It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this particular area or those interested in grasping its diverse facets and exploring the latest advances on security and privacy- preserving for IoT and 5G networks.

With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of this information that can be easily accessed if not properly handled. New privacy and security measures have been developed to address this cause for concern and have become an essential area of research within the past few years and into the foreseeable future. The ways in which data is secured and privatized should be discussed in terms of the technologies being used, the methods and models for security that have been developed, and the ways in which risks can be detected, analyzed, and mitigated. The Research Anthology on Privatizing and Securing Data reveals the latest tools and technologies for privatizing and securing data across different technologies and industries. It takes a deeper dive into both risk detection and mitigation, including an analysis of cybercrimes and cyber threats, along with a sharper focus on the technologies and methods being actively implemented and utilized to secure data online. Highlighted topics include information governance and privacy, cybersecurity, data protection, challenges in big data, security threats, and more. This book is essential for data analysts, cybersecurity professionals, data scientists, security analysts, IT specialists, practitioners, researchers, academicians, and students interested in the latest trends and technologies for privatizing and securing data.